Modeling Privacy Preservation in Smart Connected Toys by Petri-Nets
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2019-01-08
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Children data privacy must be considered as integral and factored into the system design of Smart Connected Toy (SCT). The challenge is that SCTs are capable to gather significant amount volunteered and non-volunteered data, which lacks privacy considerations. It is imperative to adopt a modeling technique that autonomously preserves privacy and secure children’s data in SCT transactions. This paper surveys the current data flow modeling techniques, which most of them do not have elements to address the privacy of Personal Identifiable Information (PII). This paper shows a Petri-Net simulation which provides privacy assurance in order to minimize the risk of privacy violation of a child’s PII and related data.
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Machine Learning, Robotic, and Toy Computing, Decision Analytics, Mobile Services, and Service Science, Smart Connected Toys (SCT), Petri-Nets, Privacy, Data Flow Modeling, Simulation
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10 pages
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Proceedings of the 52nd Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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